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Researchers used evolutionary strategy algorithms to create an AI system that could gain a high score on the game Q*bert by exploiting an old bug.

AI systems have beat human players of games including chess, Go, and Pong.

An artificial intelligence (AI)-powered bot exploited a bug in popular 1980s arcade game Q*bert to gain an all-time high score, according to a paper from researchers at Germany's University of Freiburg.

The AI bot was programmed using evolutionary strategy (ES) algorithms, which include machine learning and allow the AI to learn, adapt, and change tactics depending on the situation and other players, as noted by our sister site ZDNet. ES algorithms also serve as an alternative to the more common reinforcement learning (RL) methods that have been used to train the systems that beat humans at other games.

In Q*bert, players must jump from cube to cube to change colors, while avoiding obstacles and enemies to make it to the next round. However, the AI system was able to jump quickly from cube to cube in no particular order, causing the colors to change rapidly. A bug caused the platforms to keep blinking and the AI to continue to bounce around and gain a score of nearly one million points, as reported by The Register.